NIH Public Access Author Manuscript Published in final edited form as: Mol Psychiatry. 2009 August ; 14(8): 786 795. doi:10.1038/mp.2009.11. Genomewide linkage scan of schizophrenia in a large multicenter pedigree sample using single nucleotide polymorphisms PA Holmans 1, B Riley 2, AE Pulver 3, MJ Owen 1, DB Wildenauer 4, PV Gejman 5, BJ Mowry 6, C Laurent 7, KS Kendler 2, G Nestadt 3, NM Williams 1, SG Schwab 4, AR Sanders 5, D Nertney 6, J Mallet 8, B Wormley 2, VK Lasseter 3, MC O Donovan 1, J Duan 5, M Albus 9, M Alexander 10, S Godard 11, R Ribble 2, KY Liang 12, N Norton 1, W Maier 13, G Papadimitriou 14, D Walsh 15, M Jay 7, A O Neill 16, FB Lerer 17, D Dikeos 14, RR Crowe 18, JM Silverman 19, and DF Levinson 10 1 Department of Psychological Medicine, Wales College of Medicine, Cardiff University, Cardiff, UK 2 Virginia Institute for Psychiatric and Behavioral Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond VA, USA 3 Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, USA 4 Center for Clinical Research in Neuropsychiatry, University of Western Australia, Perth, Australia 5 Center for Psychiatric Genetics, Evanston Northwestern Healthcare Research Institute and Northwestern University, Evanston, IL, USA 6 Queensland Centre for Mental Health Research and University of Queensland, Brisbane, Australia 7 Department of Child Psychiatry, Université Pierre et Marie Curie and Hôpital de la Pitiè- Salpêtrière, Paris, France 8 Laboratoire de Génétique Moléculaire de la Neurotransmission et des Processus Neurodégénératifs, Centre National de la Recherche Scientifique, Hôpital de la Pitié Salpêtrière, Paris, France 9 State Mental Hospital, Haar, Germany 10 Department of Psychiatry, Stanford University, Stanford, CA, USA 11 INSERM, Institut de Myologie, Hôpital de la Pitiè- Salpêtrière, Paris, France 12 Department of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, Baltimore MD, USA 13 Department of Psychiatry, University of Bonn, Bonn, Germany 14 Department of Psychiatry, University of Athens Medical School, Athens, Greece 15 The Health Research Board, Dublin, Ireland 16 Department of Psychiatry, Queens University, Belfast, Northern Ireland 17 Department of Psychiatry, Hadassah-Hebrew University Medical Center, Jerusalem, Israel 18 Department of Psychiatry, The University of Iowa College of Medicine, Iowa City, IW, USA 19 Department of Psychiatry, Mt. Sinai School of Medicine, New York, NY, USA Abstract A genomewide linkage scan was carried out in eight clinical samples of informative schizophrenia families. After all quality control checks, the analysis of 707 European-ancestry families included 1,615 affected and 1,602 unaffected genotyped individuals, and the analysis of all 807 families included 1900 affected and 1839 unaffected individuals. Multipoint linkage analysis with correction for marker-marker linkage disequilibrium was carried out with 5,861 single nucleotide polymorphisms (SNPs; Illumina 4.0 linkage map). Suggestive evidence for linkage (European families) was observed on chromosomes 8p21, 8q24.1, 9q34 and 12q24.1 in non-parametric and/or parametric analyses. In a logistic regression allele-sharing analysis of linkage allowing for intersite heterogeneity, genomewide significant evidence for linkage was observed on chromosome 10p12. Significant heterogeneity was also observed on chromosome 22q11.1. Evidence for linkage across family sets and analyses was most consistent on chromosome 8p21, with a one-lod support interval that does not include the candidate gene NRG1, suggesting that one or more other susceptibility loci Contact: Douglas F. Levinson, M.D., Department of Psychiatry, Stanford University, 701 Welch Rd. Suite A-3325, Palo Alto, CA 94305 (650-724-2827, fax 650-724-3263, dflev@stanford.edu).
Holmans et al. Page 2 might exist in the region. In this era of genomewide association and deep resequencing studies, consensus linkage regions deserve continued attention, given that linkage signals can be produced by many types of genomic variation, including any combination of multiple common or rare SNPs or copy number variants in a region. Keywords Genome; Human; Genotype; Humans; Schizophrenia/*genetics; Genetic Predisposition to Disease; *Linkage (Genetics) Introduction Two major methods are currently available to scan the genome to detect disease susceptibility loci: genomewide linkage studies (GWLS) and genomewide association studies (GWAS). We report here on a GWLS of eight samples of families with multiple cases of schizophrenia (SCZ) using a dense map of single nucleotide polymorphism (SNP) markers, and the companion paper 1 reports on a meta-analysis of thirty-two SCZ GWLS including the eight samples studied here. GWLS uses hundreds or thousands of DNA markers to detect the broad regions (millions of base pairs) within which there are most likely to be disease susceptibility loci, based on the pattern of within-family correlations between marker alleles and disease. GWAS uses hundreds of thousands of SNPs that tag (serve as proxies for) most of the common SNPs in the genome, to identify small regions (tens of thousands of base pairs) likely to harbor susceptibility variants. GWAS can detect loci with much weaker genetic effects if they are due to common SNPs. For common, genetically complex disorders, GWAS have proven more successful than GWLS in producing robust and well-replicated associations. 2 However, there are genetic effects for which GWLS can be more powerful, including loci with multiple rare pathogenic mutations in different families, or several different susceptibility loci in the same region. The present study is a collaboration of seven research groups using pedigree samples collected by each group 3 11 plus a publicly-available sample 12, totalling over 800 pedigrees with ill individuals in constellations that are informative for linkage analysis. We previously carried out a set of studies of candidate linkage regions. 13 16 We now report on a new genomewide linkage scan of the entire sample. Whereas previously around 70% of these families had been included in published linkage scans using microsatellite markers 3,5,6,10,11,17 19, we have now scanned all available families using a set of almost 6,000 SNP markers genotyped with high accuracy, extracting on average around 90% of the possible linkage information from these pedigrees. In analyses of 707 European-ancestry pedigrees, significant linkage accounting for cross-site heterogeneity was observed on chromosome 10p, and suggestive evidence for linkage on chromosomes 8p, 8q and 12q, as well 9q when non-european families were included. Materials and Methods Subjects The sample is described in Tables 1 and 2. Recruitment by each research group has been previously described. 3 12 Here, affected cases included probands with DSM-IIIR diagnoses of SCZ and relatives with SCZ or schizoaffective disorder, which co-segregates with SCZ in families 20 and is often not differentiated reliably from SCZ. 21 Consensus diagnoses were based on information from semi-structured interviews, psychiatric records and family informants.
Holmans et al. Page 3 Genotyping Genotyping was carried out at the Center for Inherited Disease Research (CIDR) using the Illumina GoldenGate assay 22 to analyze the Illumina version 4 linkage marker set of 6,008 SNPs. SNPs were excluded by CIDR (N=53) based on internal quality control (QC) criteria, and by the investigators (N=36) for more than 3 parent-child inheritance errors or deviation from Hardy-Weinberg equilibrium at p < 0.001, leaving 5,861 autosomal or X chromosome SNPs for analyses. decode 23 map locations were provided by Illumina. There were 0.09% missing genotypes, 0.12% Mendelian inconsistencies prior to QC checks (0.00138% in the analyzed SNPs), and 0.002% discordant genotypes in 224 blind duplicate specimens. There were 132 DNAs excluded for poor performance in genotyping of a preliminary forensic panel or the full SNP panel; and 60 for inconsistency with reported sex, Mendelian inconsistencies greater than 0.5% or sample call rates less than 98%. Pedigree relationship analyses Pairwise identity-by-descent (IBD) proportions were analyzed for all pairs of subjects using PLINK 24, and differences between specified and actual relationships within families were analyzed using PREST. 25 As a result, 50 DNAs were excluded to resolve pairs of identical specimens, 3 families were excluded because genotypic relationships did not fit the family and 8 because the same family was found in two different samples (JHU-NIMH, JHU-ENH, ENH- NIMH or Cardiff-VCU). Pedigree structures were also corrected (e.g., half-sib vs. full-sib relationships) as required. Because of the high accuracy of genotyping with a dense SNP map that facilitated analysis of relationships, and the enlarged samples, the present data replace previous analyses of candidate regions by this collaboration for this narrow phenotypic model. 13 16 Assignment of families to ancestry subsamples Statistical analyses Families were assigned to predominantly European (EUR), African-American or African- European (AFR), or other (OTH) groups based on STRUCTURE 26 analysis of 49 independent autosomal SNPs which had large allele frequency differences between ancestries (0.5 0.69 EUR vs. AFR, 0.3 0.47 for EUR vs. OTH) in this sample based on investigatorreported ancestries, or based on public databases. EUR or AFR families had an estimated 70% or more ancestry from that group, otherwise the family was considered OTH. Members of these groups had a mean 98% or 96% ancestry, respectively, from that group. Analyses were carried out for EUR families and then for ALL families (using allele frequencies estimated separately for EUR, AFR and OTH groups 27 ). The planned primary multipoint linkage analysis of EUR families used the S PAIRS statistic (Z LikelihoodRatio and its Kong-Cox equivalent lod score 28 under the exponential model) computed with MERLIN 29 using MERLIN s correction for LD within clusters of markers based on a threshold of r 2 greater than 0.05 for consecutive pairs of markers 30. Prior to analyses, unlikely genotypes were detected and excluded using MERLIN. 31 Additional analyses included: (1) S PAIRS analysis of ALL families using ALLEGRO 2.0 32 (analyzing each ancestry subset with it own allele frequencies) with a no-ld map of 4,365 autosomal and X chromosome SNPs with no marker-marker r 2 greater than 0.05 (because ALLEGRO cannot correct for LD); (2) the Kong-Cox exponential S ALL statistic which gives more weight to larger families (results were similar and are not shown here, but are included in online supplementary files); (3) parametric heterogeneity lod score (hlod) analysis under dominant (risk allele frequency = 0.05; penetrances = 0, 0.001 and 0.001) and recessive (risk
Holmans et al. Page 4 Data sharing Results allele frequency = 0.1, penetrances = 0, 0 and 0.001) models, using MERLIN for EUR and ALLEGRO (and the no-ld map) for ALL families; (3) logistic regression analysis of IBD sharing 33,34 to assess heterogeneity across sites, linkage while accounting for heterogeneity, effects of parent-of-origin of each allele and of sex of the affected pair (M-M, M-F, F-F), and interactions between linkage regions (see online Supplementary Table 5 for description). Thresholds for significant (0.05 or fewer peaks expected genomewide per genome scan) and suggestive (less than 1 peak per scan) evidence for linkage were determined by simulation for nonparametric and parametric analyses analysis using data generated under the assumption of no linkage. Peaks were defined as local maxima at least 30 cm from another peak. The empirical threshold for parametric analysis was corrected for two tests by taking the maximum result of the dominant and recessive analyses of simulated replicates at each point. All genotypic data for this study will be made available to qualified scientists by the NIMH Center for Genetic Studies (nimhgenetics.org). Nonparametric and parametric linkage analyses The empirical lod or hlod thresholds for suggestive linkage were 1.94 for nonparametric and 2.21 for parametric tests, or 3.26 and 3.66 for significant linkage. Mean information content was 0.88 (S.D. 0.026) using MERLIN s entropy measure (reflecting potential information with fully informative markers) and 0.908 (SD, 0.028) using ALLEGRO s exponential measure (measuring potential information given the constellation of genotyped relatives). Figure 1 shows Kong-Cox lods and dominant and recessive hlod scores for EUR and ALL families. Table 2 lists the maximum lod and hlod scores in each analysis on each chromosome. The nonparametric analysis of EUR families, considered the primary analysis here, produced suggestive evidence for linkage on chromosome 8p21 (in EUR families, lod = 2.00, 45.9 cm; in ALL families, lod = 2.51, 46.4 cm, with the latter, larger score at 26.61 bp). The dominant and recessive analyses were considered an alternative approach, and suggestive evidence for linkage (taking both tests into account as noted above) was observed on chromosomes 8p21, 8q24.1, 9q34 and 12q24.1 in non-parametric and/or parametric analyses (see Table 1 for details). Evidence for linkage was most consistent for chromosome 8p21 (five of the six analyses). Heterogeneity and linkage allowing for heterogeneity Table 3 shows the results of the logistic regression analysis of linkage while allowing for intersite heterogeneity, in EUR families. Highly significant genomewide evidence for linkage with heterogeneity was observed on chromosome 10p12 (see Table 3 legend for additional details). Chromosome 8p21 again produced suggestive evidence for linkage both with and without heterogeneity in this analysis. Results of tests for intersite heterogeneity (i.e., the difference between lods with and without allowing for heterogeneity) are shown in online Supplementary Table 1. Significant heterogeneity was observed on chromosome 10p (45.6 cm) and 22q11.1 (0 cm). Supplementary online files provide details of parametric and nonparametric linkage scores, genetic location and information content for each analyzed point for each analysis in the entire sample for EUR and ALL families, as well as the full and No-LD marker maps. Online files for the companion meta-analysis paper 1 provide ranked results for each of our 8 samples separately and for EUR and ALL families separately.
Holmans et al. Page 5 Other analyses Discussion No significant chromosome-wide effects were observed for sex of the affected pair or parent of origin (online Supplementary Tables 3 and 4). Online Supplementary Table 5 shows results of interaction analyses for all pairs of 18 regions with Kong-Cox lod scores greater than 1. No genomewide significant interactions were observed. The online table legend includes a list of the most significant empirical interaction p-values. Suggestive evidence for linkage was detected on chromosome 8p21 in multiple analyses: in nonparametric, dominant and recessive analyses of 707 European-ancestry families, and in nonparametric and dominant analyses of all 807 families. This same region produced suggestive evidence for linkage (and the largest peak), in the independent Molecular Genetics of Schizophrenia (MGS) sample 35 of 409 European-ancestry and African American families. Our peak results were between 45.9 46.8 cm (between rs1561817 and rs9797, 26.59 27.65 Mb; decode linkage map and genome build 36.3 physical locations). The MGS peak was at 43.3 cm for all families (near rs196886 at 24.79 Mb), while in European-ancestry families it was at 15.3 cm (8p23, near rs7834209 at 6.9 Mb), with a slightly smaller peak at 34.6 cm (8p21, near rs34393111 at 20.28 Mb), and suggestive evidence for linkage extended beyond our peak scores. Pulver and colleagues were the first to report preliminary 36 and then strongly suggestive evidence 10 for linkage of SCZ to chromosome 8p markers in much of the JHU sample that is included here. We previously reported support for 8p linkage in a study of microsatellite markers in a majority of the families in the present analysis 13, consistent with results in this enlarged sample. The most widely-studied 8p candidate gene is NRG1 (neuregulin 1), found to be associated with SCZ by Stefansson et al. 37 in a linkage disequilibrium mapping study of a suggestive linkage peak observed in Icelandic families (there were two 8p peaks in that analysis, with the second one closer to ours), with supportive evidence in some datasets. 38 There are several indications that, if there is linkage on chromosome 8p, it is not entirely explained by NRG1. Here, lod scores within one unit of the maximum (1-lod interval) were observed between 21.37 29.36 Mb, whereas NRG1 is between 32.53 32.74 Mb. (The 1-lod interval is a reliable confidence interval in studies of Mendelian disorders, but not for complex disorders.) In the companion meta-analysis paper 1, the second bin on chromosome 8 (8.2, 28.1 56.2 cm, ~ 15.7 33 Mb) produced the strongest (suggestive) evidence for linkage in 22 European-ancestry datasets, and was ranked eighth in the analysis of all 32 datasets. NRG1 is at the centromeric edge of that bin (~ 55.7 cm), so one would expect that if it explained the linkage, the signal would extend equally in the centromeric and telomeric directions, but support for linkage was not observed in more centromeric bins (bin 8.3 in the primary analysis, from 56.2 84.3 cm; bin 8.4 in the 20 cm analysis from 56.2 75 cm; or bin 8.3 in the 30 cm shifted analysis from 42.15 70.25 cm). 1 We hypothesize that there is weak linkage to SCZ on chromosome 8p, due to one or more loci in which there are multiple rare risk-associated SNPs and/or structural variants and/or multiple associated common SNPs. There are other candidate genes on 8p (see discussion in the meta-analysis paper 1 ), it is not yet clear what accounts for the evidence for linkage in this region. Suggestive evidence for linkage was observed on chromosome 9q in the dominant analysis of all families. Support for this region in other analyses was modest, but not substantially different than the evidence for 8p. This region is not supported by previous linkage findings or the metaanalysis. 1
Holmans et al. Page 6 Genomewide significant evidence for linkage allowing for intersite heterogeneity was observed on chromosome 10p12 at 45.6 cm (21.28 Mb). We previously reported modest evidence for heterogeneity in this region 14, and in that report we also reviewed the evidence for 10p linkage reported previously in the NIMH-SGI, VCU/Ireland and part of the Bonn/Perth samples studied here. A significant signal is now seen in the present expanded sample, with a denser marker map, due to allele sharing in the Paris/CNRS, NIMH-SGI and (to a lesser degree) the VCU samples (online Supplementary Table 2). There is no indication of a high-penetrance signal from a small subset of families: the NIMH sample includes small nuclear families from the general U.S. population; and although there are some large, extended pedigrees in the Paris/ CNRS sample from La Réunion Island, most of the families with positive lod scores were small families from the general French population, and no single family had a lod score (Kong-Cox, dominant or recessive) greater than 1.4. Because we combined families from eight previouslycolected datasets, we do not have a consistent set of clinical ratings across samples to search for a possible clinical basis for linkage heterogeneity. The 10p peak is not supported by metaanalysis 1, and is far from the chromosome 10q peaks observed between 100 110 cm in two independent studies 39,40. Significant heterogeneity (but not linkage with heterogeneity) was seen on chromosome 22q at 15 Mb, adjacent to the typical region (17 21 Mb) of the 22q11 deletion syndromes whose manifestations include SCZ in approximately 20% of cases. 41 This deletion was detected in less than 0.5% of SCZ cases in two recent large studies. 42,43 No consistent association signals have been observed to date between SCZ and common SNPs in candidate genes within the deletion region. Two other regions, on chromosomes 8q24.1 and 12q24.1, produced suggestive evidence for linkage in at least one analysis, both reportedly linked to mood disorders rather than SCZ. On 8q, a combined analysis of genotypes from 11 linkage scans (1,067 families) produced a nonparametric lod score of 3.40 at 134.5 Mb, just telomeric to our 1-lod interval, in an analysis of bipolar-i and bipolar-ii cases, but the signal was much smaller in an analysis of only bipolar- I. 44 Given that by definition only bipolar-i can include psychosis (usually in around half of cases), one would not predict that the same locus in this region would account for linkage signals to bipolar disorder and SCZ. On chromosome 12q, there have been reports of linkage to major depressive 45,46 and bipolar disorders (see review by Barden et al. 47 ) with peak locations ranging from 97.4 126.5 Mb -- 116 126 Mb in bipolar studies, close to our peak at 111 Mb. Neither region was supported by the SCZ linkage meta-analysis. 1 In the linkage meta-analysis 1, genomewide significant evidence for linkage was detected on chromosome 2q (132 162 cm, 121 152 Mb), with some support for linkage across a broad region (118 176 cm and 206 235 cm). In the present study, we see a jagged line across chromosome 2q (Figure 1), reflecting diverse peaks in different samples, although without statistically significant evidence for heterogeneity. Our largest peak was in the nonparametric EUR analysis at 206.6 cm (210.87 Mb). Thus, in our data and in the meta-analysis of 32 datasets, linkage evidence on 2q is intriguing but poorly localized. Thus, in our data and in the meta-analysis of 32 datasets, linkage evidence on 2q is intriguing but poorly localized. It was recently reported that a SNP in ZNF804A, at 185 Mb on 2q, produced genomewide significant evidence for linkage when a large collaborative SCZ association sample was combined with bipolar disorders cases from the Wellcome Trust Case Control Consortium project. 48 What is the relevance of linkage studies as the field moves on to GWAS and large-scale resequencing methods? Meta-analysis provides some support for quite modest linkage signals. 1 Thus, no gene is likely to have a large effect on overall population risk. In this situation, GWAS methods have better power 2, but (currently) only for common SNPs. GWAS technologies can also detect some but not all copy number variants (CNVs). Recent studies
Holmans et al. Page 7 suggest that rare deletions on chromosomes 1q and 15q (as well as 22q11) predispose to SCZ 42,43,49, 50 ; and that SCZ cases also have a small but significant excess of very rare CNVs, some of which might therefore also be pathogenic. These findings support the more general hypothesis of multiple rare genomic events (SNPs, CNVs, other structural changes) influencing risk for a common disease. 51 53 High-penetrance CNVs like those on 1q and 15q have effects such as mental retardation and/ or autism, consistent with the observation that they reduce fertility and thus are usually de novo mutations rather than transmitted in families. But most SCZ risk variants probably have smaller effects: the risk to probands siblings is around 5% 20, and if one allows for a small proportion of cases to be due to high-penetrance CNVs, the remaining risk should be due to lower-penetrance variants which would thus be transmitted in families. It is possible that weak SCZ linkage signals are in regions where there are multiple rare as well as common risk variants, whose aggregate frequency and effects are sufficient to produce a linkage signal, and whose effects on fertility are not too severe. We refer here both to deleterious transmitted and/ or recurring sequence and structural polymorphisms with low population frequencies, and to very rare and thus very deleterious variants that segregate in different families, i.e., extreme allelic heterogeneity. One approach to finding these variants would be high-throughput resequencing studies of linkage regions. For example, significant differences have been found in the proportions of high- and low-risk individuals carrying very rare non-synonymous coding SNPs for some diseases. 54 55 This approach has not yet been attempted for schizophrenia in a large sample, thus we lack information to predict the power or optimal design of such studies. If a region in fact contained a sufficient number of rare high-risk variants to produce a linkage signal, then it might be possible to detect them via resequencing, although success would depend on the the proportion of subjects of families carrying such variants, and by the extent of locus heterogeneity, i.e., if a small proportion of cases carried rare risk variants at a large number of loci in a linkage region, studies of a feasible sample size might not detect them. It is not known whether it will prove most productive to resequence exons, entire genes with their nearby regulatory regions, or entire linkage regions (given that there are likely to be relevant unannotated intergenic regulatory sequences). Family-based samples might be particularly useful for resequencing studies of linkage peaks, if rare variants were contributing to the signal. But it also possible that because these variants are rare precisely because they reduce fertility, they could be more easily found in case-control samples, which are also larger. In our view, multiple strategies should be attempted. It has also been suggested that the power of GWAS can be increased by upweighting evidence for association based on linkage scores (resulting in a small downweighting of other regions). 56 Whether or not this formal approach is used, it would be reasonable to consider linkage findings when selecting genes and regions for dense LD mapping and large-scale resequencing studies. Supplementary Material Acknowledgments Refer to Web version on PubMed Central for supplementary material. The authors are grateful to the many family members who participated in the studies that recruited these samples. This work was supported by National Institute of Mental Health grants 7R01MH062276 (to D.F.L., C.L., M.O. and D.W.), 5R01MH068922 (to P.G.), 5R01MH068921 (to A.E.P.) and 5R01MH068881 (to B.R.). For the NIMH sample, data and biomaterials were collected in three projects that participated in the National Institute of Mental Health (NIMH) Schizophrenia Genetics Initiative. From 1991 97, the Principal Investigators and Co-Investigators were: Harvard
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Holmans et al. Page 11 Figure 1. Genomewide linkage results Shown for 707 European ancestry families (top) and for all 807 families (bottom) are linkage results across the genome. The X-axis values are cumulative chromosomal locations in centimorgans (decode map), with chromosome boundaries shown as vertical gridlines. The Y-axis values are Kong-Cox lod scores for nonparametric analyses, or heterogeneity lod (hlod) scores for parametric analyses. Black lines represent nonparametric lod scores, red lines represent hlod scores under a dominant model, and purple lines represent hlod scores under a recessive model (see text for details of the models). Dotted lines show the empirical thresholds for genomewide suggestive evidence for linkage (less than 1 peak of this magnitude expected by chance, in the absence of linkage) for nonparametric and parametric analyses. The
Holmans et al. Page 12 parametric threshold takes into account that two such tests (dominant and recessive) were performed.
Holmans et al. Page 13 Clinical sample Table 1 European ancestry African ancestry Other ancestry All families Site Fam Aff UA All Fam Aff UA All Fam Aff UA All Fam Aff UA All Australia-US 49 114 126 240 8 24 12 36 2 5 10 15 59 143 148 291 Bonn/Perth 96 212 189 401 0 0 0 0 0 0 0 0 96 212 189 401 Cardiff 113 239 88 327 0 0 0 0 0 0 0 0 113 239 88 327 ENH/Northwestern 51 121 115 236 2 4 4 8 0 0 0 0 53 125 119 244 Paris/CNRS 29 75 68 143 8 25 29 54 26 86 91 177 63 186 188 374 Johns Hopkins 124 295 429 724 8 20 21 41 1 2 2 4 133 317 452 769 NIMH-SGI 61 142 120 262 39 107 62 169 6 12 6 18 106 261 188 449 VCU/Irish 184 417 467 884 0 0 0 0 0 0 0 0 184 417 467 884 Totals: 707 1615 1602 3217 65 180 128 308 35 105 109 214 807 1900 1839 3739 Sample sizes are shown for European ancestry (abbreviated as EUR in the text), African-American or African-European (AFR) and Other ancestry (OTH) pedigrees included in the combined analysis (ALL families). Shown are the numbers of families, genotyped affected and unaffected individuals in these families, and total numbers of DNA specimens. Approximately 70% of these subjects and pedigrees had been included in previous published genome scan analysis (see text), using less informative marker sets.
Holmans et al. Page 14 Table 2 Maximum non-parametric and parametric LOD scores on each chromosome in European-ancestry and All families European-ancestry famlies All families Kong-Cox (nonpar) Dominant Recessive Kong-Cox (nonpar) Dominant Recessive Chr cm lodsnp cm HLODSNP cm HLODSNP cm lodsnp cm HLOD SNP cm HLODSNP 1 124.1 1.24rs1517432 254.7 1.13rs528011 124.1 0.91rs1517432 122.4 0.91rs508020 254.7 0.77 rs528011 47.1 0.83rs8559 2 206.6 1.88rs1396828 206.6 1.48rs1396828 233.3 1.75rs1435850 118.1 1.52rs1026220 118.1 1.13 rs1026220 182.1 1.81rs920557 3 64.6 0.37rs1405796 18.3 0.42rs1504034 9.2 0.13rs2290610 64.6 0.33rs1405793 28.3 0.47 rs749477 9.3 0.23rs1153459 4 56.3 0.84rs12142 66.1 0.67rs1866989 180.6 1.12rs724659 202.6 0.68rs996026 65.1 0.71 rs969992 181.8 1.09rs335077 5 166.2 0.96rs1299048 161.5 1.69rs728693 168.8 0.93rs878953 161.9 1.15rs949602 161.0 2.03 rs1432812 164.4 1.13rs9216 6 33.0 0.67rs1891284 21.7 0.47rs767022 167.4 0.76rs1866896 77.9 0.73rs1409104 77.9 0.66 rs1409104 100.7 1.07rs1488318 7 12.9 0.26rs758263 8.7 0.33rs1470539 78.8 0.61rs517258 12.3 0.32rs558030 8.6 0.36 rs1470539 78.4 0.46rs2009526 8 45.9 2.00rs1561817 46.3 2.65rs1561817 133.9 2.37rs901592 46.4 2.51rs9797 46.8 2.76 rs9797 133.9 1.98rs901592 9 146.5 1.69rs886017 146.8 1.85rs12335 143.3 1.81rs10901140 146.5 1.91rs886017 146.5 2.75 rs886017 145.6 1.77rs456396 10 169.3 0.85rs1536087 43.9 1.61rs1339048 68.6 1.85rs1822861 52.9 0.74rs332188 42.8 1.26 rs729245 68.0 1.41rs1822861 11 126.4 0.17rs668183 90.0 0.13rs1278402 124.9 0.16rs596437 126.1 0.14rs668183 90.0 0.20 rs948142 124.5 0.33rs665035 12 126.7 1.39rs233722 126.7 2.25rs233722 130.0 1.14rs1920586 119.0 1.55rs1862032 126.2 1.87 rs737280 130.4 1.17rs1920568 13 58.1 0.53rs301653 12.5 0.85rs6490970 127.8 0.78rs755992 122.0 0.36rs1894758 51.2 0.60 rs1853987 127.8 0.51rs912007 14 14.8 0.52rs4982599 14.8 0.63rs4982599 58.0 1.06rs999881 72.1 0.82rs7155380 14.8 0.58 rs4982599 57.5 1.62rs999881 15 58.6 1.39rs383902 68.3 1.21rs2439378 68.7 0.86rs745103 68.3 1.63rs2439378 68.3 1.63 rs2439378 68.7 1.68rs745103 16 84.7 1.51rs149156 85.1 0.84rs1177648 111.9 1.49rs1387370 85.6 1.47rs1541979 116.4 1.23 rs2052904 111.1 1.49rs723919 17 136.9 0.48rs599314 1.0 0.50rs7813 132.4 0.82rs1062935 120.8 0.68rs454138 17.4 0.46 rs1443417 124.0 1.21rs1552173 18 97.5 0.18rs1539964 97.9 0.21rs1539964 77.6 0.52rs732982 97.8 0.36rs1539964 97.8 0.51 rs1539964 77.5 0.48rs732982 19 72.5 0.62rs1603 14.3 0.58rs352500 44.0 0.61rs273265 66.5 0.39rs268666 14.3 0.51 rs352500 42.9 0.54rs4808095 20 114.6 0.46rs379042 101.6 0.69rs1570160 101.6 0.47rs1570160 108.7 0.65rs6587239 101.4 0.73 rs1570160 101.4 0.41rs1570160 21 61.0 0.65rs875060 61.4 0.99rs875060 61.4 0.46rs875060 50.8 0.62rs2837121 50.8 0.75 rs2837121 41.0 0.15rs1892687 22 63.1 1.55rs2399153 74.5 1.93rs6520165 71.4 1.00rs739240 73.3 1.52rs137930 74.5 1.43 rs6520165 71.4 0.97rs739240 X 19.3 1.08rs1656651 14.5 1.51rs1852456 15.4 1.37rs1869588 18.9 1.22rs768567 14.2 1.67 rs1852456 15.4 1.79rs1869588 Shown are multipoint linkage scores computed with MERLIN for EUR families, correcting for marker-marker linkage disequilibrium; and with ALLEGRO for ALL families using SNPs with minimal LD (r 2 > 0.05) and separate allele frequency estimates for EUR, AFR and OTH families. Bolded scores exceed empirical suggestive evidence for linkage (1.94 for Kong-Cox; 2.21 for dominant and recessive analyses taking the two tests into account). Chr = chromosome. cm = locaton of the peak score (centimorgans). LOD = LOD score. HLOD = heterogeneity LOD. SNP = assayed single nucleotide polymorphism closest to each score. Kong-Cox = equivalent LOD for a Z-likelihood ratio score computed with the Kong-Cox exponential model. For the four regions with suggestive evidence for linkage, the physical position of the largest LOD, and 1-LOD support interval in cm and Mb (megabases), were: 8p: 27.61 Mb, 37.1 49.8 cm, 21.37 29.36 Mb; 8q: 128.06 Mb, 130.1 141.6 cm, 126.84 132.63 Mb; 9q: 133.00 Mb, 143.0 151.7 cm, 131.96 134.55 Mb; 12q: 111.08 Mb, 117.3 133.6 cm, 104.07 115.64 Mb.
Holmans et al. Page 15 Table 3 Logistic regression analysis of linkage allowing for inter-site heterogeneity Chr Linkage (homogeneity) Linkage allowing for heterogeneity max lod cm # GW Peaks max lod cm # GW Peaks 1 1.14 122.4 6.96 2.81 47.1 14.76 2 1.51 116.5 3.36 4.47 152.1 1.66 3 0.63 10.3 19.86 3.71 15.1 4.76 4 0.81 177.6 13.84 2.69 179.3 17.01 5 0.84 160.9 13.06 3.46 130.6 6.46 6 0.9 33 11.55 3.12 183.5 10.08 7 0.53 10 24.53 2.06 86.1 34.61 8 2.95 46.3 0.15 5.11 46.5 0.74 9 1.41 146.5 4.02 4.1 2.5 2.74 10 1.46 45.6 3.69 8.32 45.6 0.001 11 0.15 63.3 57.57 2.41 63.3 23.62 12 1.71 119.1 2.2 3.08 119.1 10.55 13 0.41 12.4 31.63 2.94 128.1 12.56 14 0.6 14.2 21.27 3.16 47.8 9.58 15 1.13 41.4 7.08 4.06 42.2 2.91 16 1.26 83.6 5.48 3.48 115.4 6.34 17 0.63 136.9 19.86 1.97 0.4 38.06 18 0.36 78.5 35.48 2.2 78.5 29.65 19 0.82 73 13.56 3.13 73 9.97 20 0.44 60.9 29.69 3.9 60.9 3.64 21 1.08 55 7.86 2.88 49.7 13.52 22 2.08 73.7 1.06 4.81 72.6 1.09 Shown are maximum LOD scores on each autosome, by logistic regression analysis of IBD allele sharing of affected relative pairs, assuming either homogeneity across the 8 sites (no covariates) or allowing for heterogeneity (covariates for sites, 7 df). # GW peaks refers to the number of peaks (at least 30 cm apart) of this size observed genome-wide (autosomes) in 20,000 simulated replicates of chromosome 22 followed by adjustment for autosomal genome length. Results allowing for heterogeneity on chromosome 10p12 (bold italics; at 21.275 Mb, near rs 893882) would be expected by chance once per thousand genome scans, indicating genomewide significance. Results on chromosome 8 would be expected by chance less than once per genome scan (suggestive evidence for linkage). Online Supplementary Table 2 lists IBD proportions and LOD scores by site for the peaks on chromosomes 10p and 8p.